| dc.description.abstract | Elastography is an ultrasonic imaging modality, which is useful in gaining new information about tissues and diagnosing diseases. Increasing the quality of an image allows for more accurate information to be gained from the image and better interpret the experimental results. Theoretical and simulation work has been done to determine how the parameters of an ultrasound system affect the quality of elasticity images but limited experimental validation has been performed so far. This study investigates the quality of elasticity images obtainable by using ultrasound systems with different specifications. Image quality is analyzed in terms of contrast-to-noise ratio, signal-to-noise ratio, and spatial resolution. These quality factors in elastography depend on mechanical parameters (such as applied strain and boundary conditions), acoustic parameters (such as transducer center frequency, bandwidth, etc.), and signal-processing parameters (such as window length and window separation for cross-correlation based strain estimation methods). Two ultrasound systems operating with different frequencies and bandwidths will be used, and the analysis will be carried out using theoretical and simulation software as well as experimental data. Theoretical and simulation results demonstrate that the system with higher center frequency and larger bandwidth produce elastographic images with higher quality. Experimentally, the attainable improvement is expected to be lower than the one predicted by theory and simulations. This project builds on prior theoretical research with new experimental data to demonstrate that ultrasound systems with increased ultrasonic capabilities (in terms of frequency, bandwidth, beamwidth, etc.) produce elasticity images with higher quality. As these systems are used for identification of elastographic markers in tissues such as cancers, understanding their quality limitations using a systematic study will be useful to understand and interpret future pre-clinical and clinical data. | |
